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A New Global Optimization Algorithm Inspired by Parliamentary Political Competitions

机译:由议会政治竞争激发的新全球优化算法

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A new numerical optimization algorithm inspired by political competitions during parliamentary head elections is proposed in this paper. Competitive behaviors could be observed in many aspects of human social life. Our proposed algorithm is a stochastic, iterative and population-based global optimization technique like genetic algorithms and particle swarm optimizations. Particularly, our method tries to simulate the intra and inter group competitions in trying to take the control of the parliament. Performance of this method for function optimization over some benchmark multidimensional functions, of which global and local minimums are known, is compared with traditional genetic algorithms.
机译:本文提出了一种由政治竞争激发的新的数值优化算法。在人类社交生活的许多方面,可以观察到竞争行为。我们所提出的算法是一种随机,迭代和基于人口的全局优化技术,如遗传算法和粒子群优化。特别是,我们的方法试图模拟努力控制议会的竞争中的内部和间竞争。在一些基准多维函数上,这种方法优化方法的性能,其中已知全局和局部最小值,与传统的遗传算法进行比较。

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